Headquartered in Zeeland, Michigan, Herman Miller is one of the world’s largest producers of high-end office furnishings. The company’s ergonomic office chairs are used in modern workspaces around the globe.

Herman Miller provides a wide array of customization and configuration options for each piece of furniture, including an extensive catalog of over 30,000 fabrics.

Every individual piece of fabric used in a product undergoes extensive human verification to ensure the correct fabric is used and no defects are present. Some fabrics, however, are very similar, with differences scarcely visible to the human eye.

Our Computer Vision for Furniture Manufacturing system utilizes machine learning to verify fabric color and pattern on each piece of furniture that passes through the assembly line.

First, Herman Miller’s entire fabric catalog is analyzed to enable our system to know what fabrics are available.

When a panel passes through the assembly line, a barcode is scanned, processed, and an image of the furniture is taken and sent to our system. This barcode indicates what fabric should be present. If there is an error, the fabric and the barcode will not match.

The verification results are displayed for Herman Miller operators on our web dashboard. If an error is detected, the operator can rectify the problem before the product is shipped. Our system removes human errors that might occur from similar looking fabrics.

The Computer Vision for Furniture Manufacturing system uses Tensorflow and SageMaker to handle color and pattern verification. Flask, which is hosted on Amazon Web Services, provides a web interface to display verification results. A Raspberry Pi, barcode scanner, camera, and a light system are used to take consistent photographs on the assembly line and upload them to Amazon Web Services for analysis and verification.